Mapping VMEs FAO DSF Guidelines and actions taken by RFMOs … · 2019. 3. 20. · Mapping VMEs First Meeting of the Protected Areas and Ecosystems Working Group (PAEWG1) FAO workshop

Mapping VMEs

First Meeting of the Protected Areas and Ecosystems Working Group (PAEWG1)

FAO workshop on vulnerable marine ecosystems (VMEs) for the SIOFA region

18-19 March, 2019

National Research Institute of Fisheries Science, Yokohama, Japan

Ashley A. Rowden

FAO DSF Guidelines and actions taken by RFMOs in other regions

Outline

• FAO Guidelines

• NAFO

• SPRFMO

• Mapping VME issues

• Recent developments and future directions

Background

• Bottom trawling impacts seafloor habitats, communities and species

• UNGA passed resolutions to protect VMEs in 2006 and 2009

• RFMOs obliged to prevent SAI to VMEs

• FAO produces guidelines in 2009 to assist RFMOs

untrawled

trawled

FAO Guidelines

The role of the Guidelines is to provide tools, including

guidance on their application, to facilitate and encourage the

efforts of States and RFMO/As towards sustainable use of

marine living resources exploited by deep-sea fisheries, the

prevention of significant adverse impacts on deep-sea VMEs

and the protection of marine biodiversity that these ecosystems

contain.

FAO Guidelines

12. In order to achieve these objectives, States and

RFMO/As should:

…

ii. identify areas where VMEs are known or likely to occur;

…

47. Flag States and RFMO/As should conduct assessments to

establish if deep-sea fishing activities are likely to produce

significant adverse impacts in a given area. Such an impact

assessment should address, inter alia:

…

iii. identification, description and mapping of VMEs known or

likely to occur in the fishing

area;

…

FAO Guidelines

FAO Guidelines

32. Sufficiently fine-scaled data are required as a basis for the

assessment of stock status and impacts on VMEs. In addition,

fishery-independent research surveys are encouraged, in particular

to provide relevant information on VMEs and how they are

affected by anthropogenic activities.

44. As a necessary step towards the identification of VMEs,

States and RFMO/As, and as appropriate FAO, should assemble

and analyse relevant information on areas under the competence

of such RFMO/As or where vessels under the jurisdiction of

such States are engaged in DSFs or where new or expanded

DSFs are contemplated.

45. Where site-specific information is lacking, other information

that is relevant to inferring the likely presence of vulnerable

populations, communities and habitats should be used.

FAO Guidelines

To avoid SAI on VMEs, RFMOS should:

• Identify areas where VMEs are known or likely to occur

➢Use data from stock assessment surveys, independent surveys, fisheries bycatch

➢ Infer distribution of VMEs where data lacking

How do you identify areas where VMEs are known or likely to occur?

Northwest Atlantic Fisheries Organisation South Pacific Regional Fisheries Management Organisation

Examples from…

NAFO

• Biomass and species richness distribution of VME indicator taxa

• Kernel density approach to identify concentrations of VME indicator taxa

• Canadian and Spanish/EU bycatch data for – sponges, corals, seapens

Murillo et al. (2011)

Sample locations

Murillo et al. (2011)

Biomass Species richness

Biomass and species richness distribution

Kernel density

Kenchington et al. (2014)

• Identifies ‘hotspots’ based on a neighbourhood approach using a spatially-defined threshold

• Software used in GIS to automate production of the polygon surfaces for range of thresholds to identify most appropriate threshold of ‘natural’ concentrations

Kernel density


• Kernel density map showing 75 kg threshold used to define VMEs and range of other biomass thresholds

• Cross-checked against other criteria and data

SPRFMO

• Habitat suitability modellingof VME indicator taxa

• Trialled different scales of HSM

• Mostly NZ and Australian data for 10 VME indicator taxa, including corals, sponges etc Anderson et al (2016a)

Corals

Field records for species or community and maps of environment

Map of probability that species or community is present

Statistical model(including internal validation)

Habitat suitability modelling(also known as Species Distribution Modelling)

Habitat suitability modelling

• SPRFMO-scale models

• Ground truth validation revealed poor performance

• Mostly related to inaccurate global bathymetry

Anderson et al (2016a)


• NZ-regional models

• Performed better (internal validation only) using regional bathymetry

• Mapped model uncertainty

• But map did not include all areas of interest

uncertainty

Goniocorelladumosa

Anderson et al (2016b)


• SW Pacific-scale models

• Three types of models -RF, BRT, MaxEnt – for each VME indicator taxon

• Also mapped model uncertainty

Georgian et al (2019)


• Many different types of HSM models – which should you use?

• Ensemble approach combines models by averaging output weighted by individual model performance

MaxEnt

RF

BRT

Ensemble

Solenosmilia variabilis




• Calculated CV (from bootstrapping) as metric of model uncertainty –projected spatially

• There are other ways to measure uncertainty

• Important to do


Ensemble

EnsembleSpatial CV

Finally….

Acknowledge the fundamental issue with models but emphasise their purpose

“Essentially, all models are wrong, but some are useful.”

George Box

Mapping VME issues

• Are the mapped VMEs connected or isolated? –need to know the likely extent of connectivity among VMEs in different areas

e.g., VMEs in some areas will be more or less important for providing recruits to sustain overall population in region, and recovery in disturbed areas – and thus more important to protect from trawling impacts

?

Recent developments and future directions

Determining VME connectivity

• NAFO area study

• Determine connectivity of VME indicator taxa among closed areas to assess their effectiveness




• Biologically parametrised particle tracking models

• Determine spatial and temporal dispersal paths of theoretical larvae from closed areas


Surface water 100 m



• Hindcast dispersal models to assess the source of larvae for the the closed areas

• Potential source populations inferred from habitat suitability models

Sponges




• Dispersal models indicate a degree of connectivity among closed areas, with some areas being key suppliers of recruits

• Hindcasting indicates that some recruitment likely from VMEs outside of closed areas


Mapping VME issues

• Are we actually mapping VMEs? – need to identify abundance or biomass thresholds that relate to the FAO’s VME functional criteria

e.g., structurally complex VMEs should be “created by significant concentrations of biotic and abiotic features”, and that “such ecosystems often have high diversity, which is dependent on the structuring organisms”


Identifying thresholds

• Seamount-scale models

• 25 m resolution

• Based on image records and bathymetric variables derived from MBES data

Rowden et al. (2017)



• Ensemble P/A and abundance models

• Applied a subjective/expert density threshold to abundance models to identify coral reef VMEs





• Application of threshold identifies only small areas of patch reefs

• But these VME maps depend on the veracity of threshold definition

Coral reef VME




• A later comparison of P/A and abundance models indicates that perhaps threshold is ok

• New work trying to establish link between abundance and function of VME (i.e. elevated biodiversity)

Rowden et al. (in prep.)

Spe

cies

ric

hn

ess

Number of coral heads

Pro

bab

ility

of

HS

Modelled data for Forde


% Mud

• Improve mismatch between scale of environmental predictors and biological records/response

• Incorporate uncertainty in environmental predictor variables in models


• Model and map recovery potential of VMEs

• Predict and map effect of future climate change on HS for VMEs

Anderson et al. (2015)

Thank you

Documents

Mapping VMEs FAO DSF Guidelines and actions taken by RFMOs … · 2019. 3. 20. · Mapping VMEs First Meeting of the Protected Areas and Ecosystems Working Group (PAEWG1) FAO workshop